Magali Verdonck

Infrared imaging in breast cancer: automated tissue component recognition and spectral characterization of breast cancer cells as well as the tumor microenvironment

Current evaluation of histological sections of breast cancer samples remains unsatisfactory. The search for new predictive and prognostic factors is ongoing. Infrared spectroscopy and its potential to probe tissues and cells at the molecular level without requirement for contrast agents could be an attractive tool for clinical and diagnostic analysis of breast cancer. In this study, we report the successful application of FTIR (Fourier transform infrared) imaging for breast tissue component characterization. We show that specific FTIR spectral signatures can be assigned to the major tissue components of breast tumor samples. We demonstrate that a tissue component classifier can be built based on a spectral database of well-annotated tissues and successfully validated on independent breast samples. We also demonstrate that spectral features can reveal subtle differences within a tissue component, capturing for instance lymphocytic and stromal activation. By investigating in parallel lymph nodes, tonsils and wound healing tissues, we prove the uniqueness of the signature of both lymphocytic infiltrate and tumor microenvironment in the breast disease context. Finally, we demonstrate that the biochemical information reflected in the epithelial spectra might be clinically relevant for the grading purpose, suggesting potential to improve breast cancer management in the future.

The effect of anticancer drugs on seven cell lines monitored by FTIR spectroscopy.

Systemic approaches such as metabolomics are increasingly needed to improve the development of novel drugs. In this paper, we suggest a new strategy based on infrared spectroscopy which probes the global chemical composition of a sample. Seven cell lines from three tumour types were investigated and exposed to four classical anticancer drugs belonging to two classes characterized by a unique mechanism. First, each cell line was considered separately and a hierarchical clustering was built for the seven cell lines. Spectra clustered according to the drug mechanism of action for all the cell lines tested. Second, the similarities among drug mechanism spectral fingerprints were investigated for all the cell lines simultaneously. Difference spectra (the mean spectrum of the corresponding untreated cell line was subtracted) were computed so that the particular contribution of every cell line was eliminated and only the drug-induced differences could be compared. The hierarchical clustering shows a clear tendency to distinguish the two modes of action, revealing a very similar type of response to molecules with a similar mechanism. High throughput systems with 96-well plates are now available and a well established bioassay could be developed in order to provide an objective classifier for potential anticancer drugs.

Characterization of human breast cancer tissues by infrared imaging

Fourier Transform InfraRed (FTIR) spectroscopy coupled to microscopy (IR imaging) has shown unique advantages in detecting morphological and molecular pathologic alterations in biological tissues. The aim of this study was to evaluate the potential of IR imaging as a diagnostic tool to identify characteristics of breast epithelial cells and the stroma. In this study a total of 19 breast tissue samples were obtained from 13 patients. For 6 of the patients, we also obtained Non-Adjacent Non-Tumor tissue samples. Infrared images were recorded on the main cell/tissue types identified in all breast tissue samples. Unsupervised Principal Component Analyses and supervised Partial Least Square Discriminant Analyses (PLS-DA) were used to discriminate spectra. Leave-one-out cross-validation was used to evaluate the performance of PLS-DA models. Our results show that IR imaging coupled with PLS-DA can efficiently identify the main cell types present in FFPE breast tissue sections, i.e. epithelial cells, lymphocytes, connective tissue, vascular tissue and erythrocytes. A second PLS-DA model could distinguish normal and tumor breast epithelial cells in the breast tissue sections. A patient-specific model reached particularly high sensitivity, specificity and MCC rates. Finally, we showed that the stroma located close or at distance from the tumor exhibits distinct spectral characteristics. In conclusion FTIR imaging combined with computational algorithms could be an accurate, rapid and objective tool to identify/quantify breast epithelial cells and differentiate tumor from normal breast tissue as well as normal from tumor-associated stroma, paving the way to the establishment of a potential complementary tool to ensure safe tumor margins.

Abstract A34: Characterization of tumor infiltrating lymphocytes in human breast cancer by infrared imaging

In human breast cancer spatially organized Tumor Infiltrating Lymphocytes (TILs) have been associated with effective therapeutic responses and favorable clinical outcomes.[1-3] This study investigates the potential for using InfraRed (IR) imaging to identify and characterize infiltrating lymphocytes in breast tumors, focusing on CD4+, CD8+ T lymphocytes and B lymphocytes (CD20+). Fourier Transform InfraRed (FTIR) spectroscopy coupled with microscopy is an emerging tool in cancer research and diagnosis.[4,5] IR imaging can probe the chemical composition and molecular structure of cells and tissues, thereby providing a global and unique signature for all cellular constituents. Compared with standard techniques used for identification and characterization of immune cells in tissue sections, IR imaging has numerous advantages, including no requirement for staining or automation. In this study, infrared spectra of lymphocyte subpopulations were recorded for lymphocytes in FFPE tissue sections from tonsils and breast tumors. Samples were deposited on a BaF2 window and the spectroscopic imaging data acquired in transmission mode using a Hyperion imaging system (Bruker) equipped with a focal plane array detector. The specific lymphocyte subpopulations present in each region were evaluated using hematoxyline & eosin (HE) and immunofluorescent (IF) staining of adjacent tissue sections. Statistical analyses indicate that IR spectra obtained from the CD4+, CD8+ or CD20+ lymphocyte subpopulations in tonsils are significantly different and identifiable relative to the other subpopulations. These data suggest that FTIR imaging can be used to identify specific lymphocyte subpopulations in tissues based on their spectral features. Our current work is testing this hypothesis to examine immune infiltrates in breast tumor tissue and these data will be presented at the meeting. [1] C. Gu-Trantien et al. 2013. J. Clin. Invest. 2013, 123(7) pp. 2873–2892. [2] C. Gu-Trantien and K. Willard-Gallo. Oncoimmunol. 2013, 2(10):e26066. [3] C. Denkert et al., J. Clin. Oncol. 2010, 28(1), pp. 105-113. [4] G. Bellisola and C. Sorio, Am J. Cancer Res. 2012, 2(1), pp. 1-21. [5] J. Nallala et al., Cytometry A. 2013, 83(3), pp. 294-300. Citation Format: Magali Verdonck, Soizic Garaud, Laurence Buisseret, Hugues Duvillier, Christine Desmedt, Roland de Wind, Christos Sotiriou, Karen Willard-Gallo, Erik Goormaghtigh. Characterization of tumor infiltrating lymphocytes in human breast cancer by infrared imaging. [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy: A New Chapter; December 1-4, 2014; Orlando, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2015;3(10 Suppl):Abstract nr A34.